Overview

Dataset statistics

Number of variables14
Number of observations2159
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory244.7 KiB
Average record size in memory116.1 B

Variable types

Numeric4
Text2
Categorical5
DateTime3

Dataset

Description신청번호,사건순번,사건명,상태명,신청인수,입력일시,신청구분,신청인 법인 여부,피신청인 법인 여부,피해금액,신청일,수수료,수정일시,구비서류우편송달여부
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16716/S/1/datasetView.do

Alerts

신청번호 is highly overall correlated with 상태명High correlation
피해금액 is highly overall correlated with 수수료High correlation
수수료 is highly overall correlated with 피해금액High correlation
상태명 is highly overall correlated with 신청번호High correlation
신청인 법인 여부 is highly imbalanced (83.6%)Imbalance
피해금액 has 127 (5.9%) zerosZeros

Reproduction

Analysis started2023-12-11 04:35:55.001931
Analysis finished2023-12-11 04:35:58.916305
Duration3.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신청번호
Real number (ℝ)

HIGH CORRELATION 

Distinct2139
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1595207.3
Minimum610001
Maximum2230064
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.1 KiB
2023-12-11T13:35:58.993849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum610001
5-th percentile730022.9
Q11330039.5
median1630107
Q31930075.5
95-th percentile2130124.1
Maximum2230064
Range1620063
Interquartile range (IQR)600036

Descriptive statistics

Standard deviation425250.5
Coefficient of variation (CV)0.26658008
Kurtosis-0.5758907
Mean1595207.3
Median Absolute Deviation (MAD)300018
Skewness-0.57344656
Sum3.4440526 × 109
Variance1.8083799 × 1011
MonotonicityNot monotonic
2023-12-11T13:35:59.188108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2130004 2
 
0.1%
2230030 2
 
0.1%
2110015 2
 
0.1%
2230049 2
 
0.1%
2230018 2
 
0.1%
2130008 2
 
0.1%
2230037 2
 
0.1%
2130148 2
 
0.1%
2030082 2
 
0.1%
2230043 2
 
0.1%
Other values (2129) 2139
99.1%
ValueCountFrequency (%)
610001 1
< 0.1%
620001 1
< 0.1%
630001 1
< 0.1%
630002 1
< 0.1%
630003 1
< 0.1%
630004 1
< 0.1%
630005 1
< 0.1%
630006 1
< 0.1%
630007 1
< 0.1%
630008 1
< 0.1%
ValueCountFrequency (%)
2230064 1
< 0.1%
2230062 1
< 0.1%
2230061 1
< 0.1%
2230059 1
< 0.1%
2230058 2
0.1%
2230057 1
< 0.1%
2230054 1
< 0.1%
2230053 1
< 0.1%
2230052 1
< 0.1%
2230051 1
< 0.1%

사건순번
Text

Distinct2139
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
2023-12-11T13:35:59.608016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.9726725
Min length6

Characters and Unicode

Total characters15054
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2119 ?
Unique (%)98.1%

Sample

1st row20-1-19
2nd row20-1-36
3rd row21-3-7
4th row20-1-21
5th row21-3-12
ValueCountFrequency (%)
21-3-4 2
 
0.1%
21-3-150 2
 
0.1%
22-3-37 2
 
0.1%
21-3-130 2
 
0.1%
22-3-34 2
 
0.1%
21-3-128 2
 
0.1%
21-1-2 2
 
0.1%
22-3-28 2
 
0.1%
22-3-30 2
 
0.1%
22-3-18 2
 
0.1%
Other values (2129) 2139
99.1%
2023-12-11T13:36:00.208618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 4318
28.7%
1 3171
21.1%
3 2240
14.9%
2 1213
 
8.1%
0 736
 
4.9%
8 619
 
4.1%
9 595
 
4.0%
4 580
 
3.9%
7 551
 
3.7%
5 521
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 10736
71.3%
Dash Punctuation 4318
28.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3171
29.5%
3 2240
20.9%
2 1213
 
11.3%
0 736
 
6.9%
8 619
 
5.8%
9 595
 
5.5%
4 580
 
5.4%
7 551
 
5.1%
5 521
 
4.9%
6 510
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 4318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15054
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 4318
28.7%
1 3171
21.1%
3 2240
14.9%
2 1213
 
8.1%
0 736
 
4.9%
8 619
 
4.1%
9 595
 
4.0%
4 580
 
3.9%
7 551
 
3.7%
5 521
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15054
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 4318
28.7%
1 3171
21.1%
3 2240
14.9%
2 1213
 
8.1%
0 736
 
4.9%
8 619
 
4.1%
9 595
 
4.0%
4 580
 
3.9%
7 551
 
3.7%
5 521
 
3.5%

사건명
Text

Distinct1894
Distinct (%)87.7%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
2023-12-11T13:36:00.549707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length116
Median length89
Mean length58.642427
Min length21

Characters and Unicode

Total characters126609
Distinct characters350
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1765 ?
Unique (%)81.8%

Sample

1st row강서구 oo동 건물 신축공사장의 비산먼지로 인한 정신적 피해에 대해 4000천원의 배상을 요구하는 환경분쟁(알선) 신청사건
2nd row노원구 00동 아파트 신축공사장의 소음 진동 먼지로 인한 정신적 피해에 대해 20000천 원의 배상을 요구하는 환경분쟁(알선) 신청사건
3rd row금천구 00동 오피스텔 신축공사장의 소음 먼지로 인한 정신적 피해에 대해 4500천원의 배상을 요구하는 환경분쟁(재정) 신청사건
4th row은평구 00동 재건축축공사장의 소음 진동 먼지로 인한 정신적 피해 건강상피해에 대해 34000천원의 배상을 요구하는 환경분쟁(알선) 신청사건
5th row중랑구 00동 음식점의 실외기 소음으로 인한 정신적 피해에 대해 12000천원의 배상을 요구하는 환경분쟁(재정) 사건
ValueCountFrequency (%)
인한 2058
 
8.1%
정신적 1421
 
5.6%
피해에 1197
 
4.7%
배상을 1164
 
4.6%
요구하는 1120
 
4.4%
대해 1112
 
4.4%
00동 791
 
3.1%
ㅇㅇ동 641
 
2.5%
신청사건 608
 
2.4%
신축공사장 525
 
2.1%
Other values (1606) 14817
58.2%
2023-12-11T13:36:01.194254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23421
 
18.5%
구 4364
 
3.4%
0 4281
 
3.4%
신 4221
 
3.3%
동 3938
 
3.1%
정 3567
 
2.8%
해 3360
 
2.7%
사 3084
 
2.4%
건 2633
 
2.1%
적 2364
 
1.9%
Other values (340) 71376
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92079
72.7%
Space Separator 23421
 
18.5%
Decimal Number 6450
 
5.1%
Other Punctuation 1283
 
1.0%
Close Punctuation 976
 
0.8%
Open Punctuation 976
 
0.8%
Uppercase Letter 648
 
0.5%
Other Symbol 617
 
0.5%
Lowercase Letter 134
 
0.1%
Math Symbol 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 4364
 
4.7%
신 4221
 
4.6%
동 3938
 
4.3%
정 3567
 
3.9%
해 3360
 
3.6%
사 3084
 
3.3%
건 2633
 
2.9%
적 2364
 
2.6%
로 2300
 
2.5%
피 2243
 
2.4%
Other values (303) 60005
65.2%
Uppercase Letter
ValueCountFrequency (%)
O 633
97.7%
T 2
 
0.3%
A 2
 
0.3%
L 2
 
0.3%
E 2
 
0.3%
D 2
 
0.3%
V 1
 
0.2%
R 1
 
0.2%
B 1
 
0.2%
S 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
0 4281
66.4%
5 439
 
6.8%
1 397
 
6.2%
2 318
 
4.9%
3 252
 
3.9%
4 210
 
3.3%
6 155
 
2.4%
8 143
 
2.2%
7 129
 
2.0%
9 126
 
2.0%
Other Punctuation
ValueCountFrequency (%)
? 1212
94.5%
. 62
 
4.8%
: 8
 
0.6%
' 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 973
99.7%
］ 2
 
0.2%
] 1
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 973
99.7%
［ 2
 
0.2%
[ 1
 
0.1%
Other Symbol
ValueCountFrequency (%)
○ 611
99.0%
㈜ 6
 
1.0%
Space Separator
ValueCountFrequency (%)
23421
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 134
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92085
72.7%
Common 33742
 
26.7%
Latin 782
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 4364
 
4.7%
신 4221
 
4.6%
동 3938
 
4.3%
정 3567
 
3.9%
해 3360
 
3.6%
사 3084
 
3.3%
건 2633
 
2.9%
적 2364
 
2.6%
로 2300
 
2.5%
피 2243
 
2.4%
Other values (304) 60011
65.2%
Common
ValueCountFrequency (%)
23421
69.4%
0 4281
 
12.7%
? 1212
 
3.6%
) 973
 
2.9%
( 973
 
2.9%
○ 611
 
1.8%
5 439
 
1.3%
1 397
 
1.2%
2 318
 
0.9%
3 252
 
0.7%
Other values (14) 865
 
2.6%
Latin
ValueCountFrequency (%)
O 633
80.9%
o 134
 
17.1%
T 2
 
0.3%
A 2
 
0.3%
L 2
 
0.3%
E 2
 
0.3%
D 2
 
0.3%
V 1
 
0.1%
R 1
 
0.1%
B 1
 
0.1%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90670
71.6%
ASCII 33909
 
26.8%
Compat Jamo 1409
 
1.1%
Geometric Shapes 611
 
0.5%
None 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23421
69.1%
0 4281
 
12.6%
? 1212
 
3.6%
) 973
 
2.9%
( 973
 
2.9%
O 633
 
1.9%
5 439
 
1.3%
1 397
 
1.2%
2 318
 
0.9%
3 252
 
0.7%
Other values (23) 1010
 
3.0%
Hangul
ValueCountFrequency (%)
구 4364
 
4.8%
신 4221
 
4.7%
동 3938
 
4.3%
정 3567
 
3.9%
해 3360
 
3.7%
사 3084
 
3.4%
건 2633
 
2.9%
적 2364
 
2.6%
로 2300
 
2.5%
피 2243
 
2.5%
Other values (302) 58596
64.6%
Compat Jamo
ValueCountFrequency (%)
ㅇ 1409
100.0%
Geometric Shapes
ValueCountFrequency (%)
○ 611
100.0%
None
ValueCountFrequency (%)
㈜ 6
60.0%
］ 2
 
20.0%
［ 2
 
20.0%

상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
사건종결
1765 
사건접수 및 배정
394 

Length

Max length9
Median length4
Mean length4.9124595
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사건접수 및 배정
2nd row사건접수 및 배정
3rd row사건접수 및 배정
4th row사건접수 및 배정
5th row사건접수 및 배정

Common Values

ValueCountFrequency (%)
사건종결 1765
81.8%
사건접수 및 배정 394
 
18.2%

Length

2023-12-11T13:36:01.385599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:36:01.554656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사건종결 1765
59.9%
사건접수 394
 
13.4%
및 394
 
13.4%
배정 394
 
13.4%

신청인수
Real number (ℝ)

Distinct95
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.1111626
Minimum0
Maximum1206
Zeros8
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size19.1 KiB
2023-12-11T13:36:01.723818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q34
95-th percentile24
Maximum1206
Range1206
Interquartile range (IQR)3

Descriptive statistics

Standard deviation41.498871
Coefficient of variation (CV)5.1162667
Kurtosis403.16718
Mean8.1111626
Median Absolute Deviation (MAD)1
Skewness17.328097
Sum17512
Variance1722.1563
MonotonicityNot monotonic
2023-12-11T13:36:01.958889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1052
48.7%
2 262
 
12.1%
4 221
 
10.2%
3 211
 
9.8%
5 70
 
3.2%
6 47
 
2.2%
8 26
 
1.2%
10 24
 
1.1%
9 22
 
1.0%
7 17
 
0.8%
Other values (85) 207
 
9.6%
ValueCountFrequency (%)
0 8
 
0.4%
1 1052
48.7%
2 262
 
12.1%
3 211
 
9.8%
4 221
 
10.2%
5 70
 
3.2%
6 47
 
2.2%
7 17
 
0.8%
8 26
 
1.2%
9 22
 
1.0%
ValueCountFrequency (%)
1206 1
< 0.1%
710 1
< 0.1%
670 1
< 0.1%
425 1
< 0.1%
404 1
< 0.1%
372 1
< 0.1%
289 1
< 0.1%
265 1
< 0.1%
234 2
0.1%
228 1
< 0.1%

입력일시
Date

Distinct1393
Distinct (%)64.5%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
Minimum2006-01-06 00:00:00
Maximum2022-09-21 00:00:00
2023-12-11T13:36:02.157863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:36:02.379063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신청구분
Categorical

Distinct3
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
재정
1585 
알선
488 
조정
 
86

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row알선
2nd row알선
3rd row재정
4th row알선
5th row재정

Common Values

ValueCountFrequency (%)
재정 1585
73.4%
알선 488
 
22.6%
조정 86
 
4.0%

Length

2023-12-11T13:36:02.551175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:36:03.012949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재정 1585
73.4%
알선 488
 
22.6%
조정 86
 
4.0%

신청인 법인 여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
개인
2107 
법인
 
52

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row개인
4th row개인
5th row개인

Common Values

ValueCountFrequency (%)
개인 2107
97.6%
법인 52
 
2.4%

Length

2023-12-11T13:36:03.162845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:36:03.300638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 2107
97.6%
법인 52
 
2.4%

피신청인 법인 여부
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
개인
1466 
법인
693 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인
2nd row개인
3rd row개인
4th row법인
5th row개인

Common Values

ValueCountFrequency (%)
개인 1466
67.9%
법인 693
32.1%

Length

2023-12-11T13:36:03.419501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:36:03.538278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인 1466
67.9%
법인 693
32.1%

피해금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct586
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21629199
Minimum0
Maximum1.4 × 109
Zeros127
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size19.1 KiB
2023-12-11T13:36:03.700012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14000000
median9000000
Q323725000
95-th percentile87070000
Maximum1.4 × 109
Range1.4 × 109
Interquartile range (IQR)19725000

Descriptive statistics

Standard deviation50654453
Coefficient of variation (CV)2.3419477
Kurtosis335.415
Mean21629199
Median Absolute Deviation (MAD)7000000
Skewness14.94442
Sum4.6697442 × 1010
Variance2.5658736 × 1015
MonotonicityNot monotonic
2023-12-11T13:36:03.914034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000000 273
 
12.6%
10000000 179
 
8.3%
0 127
 
5.9%
3000000 88
 
4.1%
2000000 75
 
3.5%
20000000 71
 
3.3%
30000000 47
 
2.2%
1000000 45
 
2.1%
6000000 44
 
2.0%
4000000 39
 
1.8%
Other values (576) 1171
54.2%
ValueCountFrequency (%)
0 127
5.9%
1 14
 
0.6%
10 5
 
0.2%
10000 1
 
< 0.1%
20000 1
 
< 0.1%
100000 2
 
0.1%
170000 1
 
< 0.1%
300000 7
 
0.3%
400000 2
 
0.1%
410000 1
 
< 0.1%
ValueCountFrequency (%)
1400000000 1
< 0.1%
1000000000 1
< 0.1%
531000000 2
0.1%
500000000 1
< 0.1%
456000000 1
< 0.1%
440000000 1
< 0.1%
300000000 1
< 0.1%
219971000 1
< 0.1%
210000000 1
< 0.1%
201870000 1
< 0.1%

신청일
Date

Distinct1490
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
Minimum2006-01-06 00:00:00
Maximum2022-09-16 00:00:00
2023-12-11T13:36:04.090400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:36:04.256337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

수수료
Real number (ℝ)

HIGH CORRELATION 

Distinct460
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51416.244
Minimum10000
Maximum1427500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.1 KiB
2023-12-11T13:36:04.426379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10000
Q117500
median20000
Q359750
95-th percentile199559
Maximum1427500
Range1417500
Interquartile range (IQR)42250

Descriptive statistics

Standard deviation67796.918
Coefficient of variation (CV)1.3185895
Kurtosis82.225924
Mean51416.244
Median Absolute Deviation (MAD)10000
Skewness5.5360121
Sum1.1100767 × 108
Variance4.5964221 × 109
MonotonicityNot monotonic
2023-12-11T13:36:04.629803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000 575
26.6%
10000 532
24.6%
35000 140
 
6.5%
65000 45
 
2.1%
23000 37
 
1.7%
95000 37
 
1.7%
50000 27
 
1.3%
59000 20
 
0.9%
155000 20
 
0.9%
29000 19
 
0.9%
Other values (450) 707
32.7%
ValueCountFrequency (%)
10000 532
24.6%
10300 1
 
< 0.1%
10450 1
 
< 0.1%
10780 1
 
< 0.1%
13720 1
 
< 0.1%
14500 2
 
0.1%
15190 1
 
< 0.1%
17500 5
 
0.2%
19000 1
 
< 0.1%
20000 575
26.6%
ValueCountFrequency (%)
1427500 1
 
< 0.1%
558500 2
 
0.1%
255000 12
0.6%
254990 2
 
0.1%
254940 1
 
< 0.1%
254800 1
 
< 0.1%
254000 2
 
0.1%
253000 3
 
0.1%
252744 1
 
< 0.1%
252600 1
 
< 0.1%

수정일시
Date

Distinct1345
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
Minimum2006-01-06 00:00:00
Maximum2022-09-21 00:00:00
2023-12-11T13:36:04.807276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:36:04.958274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

구비서류우편송달여부
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
1596 
송달
563 

Length

Max length2
Median length1
Mean length1.2607689
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row송달
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
1596
73.9%
송달 563
 
26.1%

Length

2023-12-11T13:36:05.095631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T13:36:05.201711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
송달 563
100.0%

Interactions

2023-12-11T13:35:58.033301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:56.099351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:56.727841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:57.341803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:58.180621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:56.262160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:56.921297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:57.526855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:58.296558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:56.416196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:57.042017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:57.685024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:58.416174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:56.574508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:57.184760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T13:35:57.875563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T13:36:05.272770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신청번호상태명신청인수신청구분신청인 법인 여부피신청인 법인 여부피해금액수수료구비서류우편송달여부
신청번호1.0000.9760.0000.2170.1290.5970.0580.1300.330
상태명0.9761.0000.0000.0000.0510.0000.0000.0910.158
신청인수0.0000.0001.0000.2140.0870.0210.8310.7510.052
신청구분0.2170.0000.2141.0000.0400.0000.2760.3900.078
신청인 법인 여부0.1290.0510.0870.0401.0000.2970.0000.0000.233
피신청인 법인 여부0.5970.0000.0210.0000.2971.0000.0000.0640.000
피해금액0.0580.0000.8310.2760.0000.0001.0000.9820.000
수수료0.1300.0910.7510.3900.0000.0640.9821.0000.112
구비서류우편송달여부0.3300.1580.0520.0780.2330.0000.0000.1121.000
2023-12-11T13:36:05.391503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
피신청인 법인 여부상태명신청인 법인 여부신청구분구비서류우편송달여부
피신청인 법인 여부1.0000.0000.1920.0000.000
상태명0.0001.0000.0330.0000.101
신청인 법인 여부0.1920.0331.0000.0670.149
신청구분0.0000.0000.0671.0000.130
구비서류우편송달여부0.0000.1010.1490.1301.000
2023-12-11T13:36:05.501733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신청번호신청인수피해금액수수료상태명신청구분신청인 법인 여부피신청인 법인 여부구비서류우편송달여부
신청번호1.000-0.033-0.0110.0340.8630.1330.0990.4600.253
신청인수-0.0331.0000.3090.3120.0000.0900.0630.0150.038
피해금액-0.0110.3091.0000.6830.0000.1190.0000.0000.000
수수료0.0340.3120.6831.0000.0500.1820.0000.0310.086
상태명0.8630.0000.0000.0501.0000.0000.0330.0000.101
신청구분0.1330.0900.1190.1820.0001.0000.0670.0000.130
신청인 법인 여부0.0990.0630.0000.0000.0330.0671.0000.1920.149
피신청인 법인 여부0.4600.0150.0000.0310.0000.0000.1921.0000.000
구비서류우편송달여부0.2530.0380.0000.0860.1010.1300.1490.0001.000

Missing values

2023-12-11T13:35:58.603261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T13:35:58.821916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

신청번호사건순번사건명상태명신청인수입력일시신청구분신청인 법인 여부피신청인 법인 여부피해금액신청일수수료수정일시구비서류우편송달여부
0201001920-1-19강서구 oo동 건물 신축공사장의 비산먼지로 인한 정신적 피해에 대해 4000천원의 배상을 요구하는 환경분쟁(알선) 신청사건사건접수 및 배정22020-07-06알선개인개인40000002020-06-29100002020-07-06
1201003620-1-36노원구 00동 아파트 신축공사장의 소음 진동 먼지로 인한 정신적 피해에 대해 20000천 원의 배상을 요구하는 환경분쟁(알선) 신청사건사건접수 및 배정12020-11-12알선개인개인200000002020-11-09100002020-11-12송달
2213000721-3-7금천구 00동 오피스텔 신축공사장의 소음 먼지로 인한 정신적 피해에 대해 4500천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정32021-01-28재정개인개인45000002021-01-20200002021-01-28
3201002120-1-21은평구 00동 재건축축공사장의 소음 진동 먼지로 인한 정신적 피해 건강상피해에 대해 34000천원의 배상을 요구하는 환경분쟁(알선) 신청사건사건접수 및 배정172020-07-21알선개인법인340000002020-07-21100002020-08-04
4213001221-3-12중랑구 00동 음식점의 실외기 소음으로 인한 정신적 피해에 대해 12000천원의 배상을 요구하는 환경분쟁(재정) 사건사건접수 및 배정12021-02-18재정개인개인120000002021-02-18410002021-02-18
5211000621-1-6중구 00동 주상복합 신축 공사장의 소음 진동 먼지로 인한 정신적 기타 피해에 대해 6000천원의 배상을 요구하는 환경분쟁(알선) 사건사건접수 및 배정22021-02-18알선개인개인60000002021-02-05100002021-02-18
6203006020-3-60종로구 00동 건물 리모델링 공사장의 소음 진동으로 인한 정신적 피해에 대해 2000천원의 배상을 요구하는 환경분쟁조정(재정)신청사건사건접수 및 배정12020-08-18재정개인개인20000002020-07-20200002020-08-18송달
7203007120-3-71강북구 00동 콘도 신축 공사장의 소음 진동 먼지로 인한 정신적건축물피해에 대해 28000천원의 배상을 요구하는 환경분쟁조정(재정)신청사건사건접수 및 배정42020-10-08재정개인개인280000002020-10-12890002020-10-08
8203005620-3-56구로구 oo동 하수도 확장공사장의 소음 진동 먼지로 인한 정신적 영업적 피해에 대해 22000천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정12020-07-08재정개인개인220000002020-07-07710002020-07-08송달
9203005520-3-55강남구 oo동 아파트 신축공사장의 소음 진동 먼지로 인한 정신적 피해에 대해 10000천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정12020-07-08재정개인개인100000002020-07-07350002020-07-08송달
신청번호사건순번사건명상태명신청인수입력일시신청구분신청인 법인 여부피신청인 법인 여부피해금액신청일수수료수정일시구비서류우편송달여부
2149223005422-3-54동작구 00동 사업장 소음으로 인한 정신적 피해에 대해 10000천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정12022-08-10재정개인개인100000002022-08-07350002022-08-10송달
2150221001222-1-12서대문구 00동 공동주택 층간소음으로 인한 정신적 피해에 대해 5100천원의 배상 및 실외기 이전 등 방음대책을 요구하는 환경분쟁(알선) 신청사건사건접수 및 배정12022-08-10알선개인개인51000002022-08-06100002022-08-10송달
2151223006222-3-62마포구 00동 공동주택 층간소음으로 인한 정신적 피해에 대해 2000천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정22022-09-14재정개인개인20000002022-06-22200002022-09-14송달
2152223005722-3-57양천구 00동 공사장 소음으로 인한 정신적 피해에 대해 2000천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정22022-08-30재정개인법인20000002022-08-18200002022-08-30
2153221001422-1-14관악구 00동 공사장 소음 진동 먼지로 인한 정신적 피해에 대해 1000천원의 배상을 요구하는 환경분쟁(알선) 신청사건사건접수 및 배정22022-08-30알선개인개인10000002022-08-19100002022-08-30송달
2154223005922-3-59강북구 00동 공동주택 층간소음으로 인한 정신적 피해에 대해 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정42022-09-02재정개인개인80000002022-08-19290002022-09-02
2155223005822-3-58종로구 00동 공동주택 층간소음으로 인한 정신적 피해에 대해 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정22022-09-02재정개인개인50000002022-08-30200002022-09-02
2156223006122-3-61강동구 00동 공사장 소음 진동으로 인한 정신적 건강상 피해에 대해 5000천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정12022-09-14재정개인개인50000002022-08-25200002022-09-14
2157223005822-3-58종로구 00동 공동주택 층간소음으로 인한 정신적 피해에 대해 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정22022-09-02재정개인개인50000002022-08-30200002022-09-15
2158223006422-3-64서대문구 00동 공사장 소음 진동 분진으로 인한 정신적 기타(건강) 피해에 대해 4500천원의 배상을 요구하는 환경분쟁(재정) 신청사건사건접수 및 배정22022-09-21재정개인개인45000002022-09-16200002022-09-21